Turing Award Goes To Machine Learning Innovator

March 10, 2011

The prestigious Alan Mathison Turing Award was awarded to a Harvard University professor whose machine learning research helped to create an IBM computer that defeated two human competitors on a recent “Jeopardy!” tournament.

Leslie Valiant, a computer science and applied mathematics professor, was honored for his “contributions to the development of computational learning theory and to the broader theory of computer science,” the Association for Computing Machinery said on Wednesday.

The $250,000 award, sponsored by chipmaker Intel and search giant Google, is considered the Nobel Prize of the computing world and is named after the famous British mathematician who worked in the field of computer science and is well-known for his role in breaking the German Enigma code during World War II.

Some of Valiant’s biggest contributions concern the mathematical foundations of computer learning, an area of study that has led to breakthroughs such as IBM’s famous computer Watson, the machine that was built to play “Jeopardy!” The computer defeated two of the game’s top winners in a display of how far computer scientists have come in programming computers to understand human language and to make decisions based on tons of data the machines are able to store.

The association also cited his contributions that have led to advancements in artificial intelligence and areas such as natural language processing, handwriting recognition and computer vision. And it also cited his influential models for “parallel computing,” or processing many different kinds of data at once rather than the one-at-a-time approach of traditional computing.

“Leslie Valiant’s accomplishments over the last 30 years have provided the theoretical basis for progress in artificial intelligence and led to extraordinary achievements in machine learning,” ACM president Alain Chesnais said.

“His profound vision in computer science, mathematics, and cognitive theory have been combined with other techniques to build modern forms of machine learning and communication, like IBM’s ‘Watson’ computing system, that have enabled computing systems to rival a human’s ability to answer questions,” Chesnais told AFP.

Intel’s Shekhar Borkar praised Valiant’s work in computation theory for having “revolutionized machine learning and artificial intelligence, making machines almost think.”

Valiant’s “Theory of the Learnable,” published in 1984 in Communications of the Association for Computing Machinery, was cited by the organization as one of the “seminal contributions to machine learning.”

The award will be presented June 4 at a ceremony in San Jose, California.

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